Complete Keras Bootcamp For Deep Learning in Python
Complete Keras Bootcamp For Deep Learning in Python, available at $54.99, has an average rating of 3.95, with 43 lectures, based on 175 reviews, and has 1062 subscribers.
You will learn about Harness The Power Of Anaconda/iPython For Practical Data Science Learn How To Install & Use Tensorflow Within Anaconda Implement Neural Network Modelling With Keras Implement Deep Learning Based Unsupervised Learning With Keras Implement Deep Learning Based Supervised Learning With Keras Implement Convolution Neural Networks With Keras This course is ideal for individuals who are People Interested In Learning Python Based Tensorflow and Keras For Data Science Applications or People With Prior Exposure To Python Programming &/Or Data Science Concepts or People Interested In Implementing Neural Networks & Deep Learning Models With Keras It is particularly useful for People Interested In Learning Python Based Tensorflow and Keras For Data Science Applications or People With Prior Exposure To Python Programming &/Or Data Science Concepts or People Interested In Implementing Neural Networks & Deep Learning Models With Keras.
Enroll now: Complete Keras Bootcamp For Deep Learning in Python
Summary
Title: Complete Keras Bootcamp For Deep Learning in Python
Price: $54.99
Average Rating: 3.95
Number of Lectures: 43
Number of Published Lectures: 43
Number of Curriculum Items: 43
Number of Published Curriculum Objects: 43
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Harness The Power Of Anaconda/iPython For Practical Data Science
- Learn How To Install & Use Tensorflow Within Anaconda
- Implement Neural Network Modelling With Keras
- Implement Deep Learning Based Unsupervised Learning With Keras
- Implement Deep Learning Based Supervised Learning With Keras
- Implement Convolution Neural Networks With Keras
Who Should Attend
- People Interested In Learning Python Based Tensorflow and Keras For Data Science Applications
- People With Prior Exposure To Python Programming &/Or Data Science Concepts
- People Interested In Implementing Neural Networks & Deep Learning Models With Keras
Target Audiences
- People Interested In Learning Python Based Tensorflow and Keras For Data Science Applications
- People With Prior Exposure To Python Programming &/Or Data Science Concepts
- People Interested In Implementing Neural Networks & Deep Learning Models With Keras
THIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH KERAS IN PYTHON!
It is a full 7-Hour Python Keras Neural Network & Deep Learning Boot Camp that will help you learn basic machine learning, neural networks and deep learning using one of the most important Deep Learning frameworks: Keras.
HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:
This course is your complete guide to practical machine & deep learning using the Keras framework in Python.
This means, this course coversthe important aspects of Keras if you take this course, you can do away with taking other courses or buying books on Python Keras based data science.
In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Keras is revolutionizing Deep Learning.
By gaining proficiency in Keras you can give your company a competitive edge and boost your career to the next level.
THIS IS MY PROMISE TO YOU: COMPLETE THIS ONE COURSE & BECOME A PRO IN PRACTICAL KERAS BASED DATA SCIENCE!
But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.
Over the course of my research, I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic and use data science interchangeably with machine learning..
This gives students an incomplete knowledge of the subject. My course, on the other hand, will give you a robust grounding in all aspects of data science within the Tensorflow framework.
Unlike other Python courses, we dig deep into the statistical modelling features of Tensorflow & Keras and give you a one-of-a-kind grounding in these frameworks!
DISCOVER 8 COMPLETE SECTIONS ADDRESSING EVERY ASPECT OF PYTHON BASED KERAS DATA SCIENCE:
• A full introduction to Python Data Science and powerful Python driven framework for data science, Anaconda
• Getting started with Jupyter notebooks for implementing data science techniques in Python
• A comprehensive presentation about Keras installation and a brief introduction to the other Python data science packages
• Brief introduction to the working of Pandas and Numpy
• The basics of the Keras syntax
• Machine Learning, Supervised Learning, Unsupervised Learning in the Keras frameworks
• You’ll even discover how to create artificial neural networks and deep learning structures with Keras
BUT, WAIT! THIS ISN’T JUST ANY OTHER DATA SCIENCE COURSE:
You’ll start by absorbing the most valuable Python Keras basics and techniques.
I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts.
My course will help youimplement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real -life.
After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python along with gaining fluency in Keras. I will even introduce you to deep learning models such as Convolution Neural network (CNN) !!
The underlying motivation for the course is to ensure you can apply Python-based data science on real data into practice today, start analyzing data for your own projects whatever your skill level, and impress your potential employers with actual examples of your data science abilities.
This course will take students without a prior Python and/or statistics background from a basic level to performing some of the most common advanced data science techniques using the powerful Python-based Jupyter notebooks
It is a practical, hands-on course, i.e. we will spend some time dealing with some of the theoretical concepts related to data science. However, the majority of the course will focus on implementing different techniques on real data and interpret the results..
After each video, you will learn a new concept or technique which you may apply to your own projects!
JOIN THE COURSE NOW!
Course Curriculum
Chapter 1: Welcome To The Course
Lecture 1: What is the Course About?
Lecture 2: Data and Code Used in the Course
Lecture 3: Why AI and Deep Learning?
Lecture 4: Get Started With the Python Data Science Environment: Anaconda
Lecture 5: Anaconda for Mac Users
Lecture 6: The iPython Environment
Chapter 2: Introduction to Python Data Science Packages
Lecture 1: Python Packages for Data Science
Lecture 2: Introduction to Numpy
Lecture 3: Create Numpy Arrays
Lecture 4: Numpy Operations
Lecture 5: Numpy for Basic Vector Arithmetic
Lecture 6: Numpy for Basic Matrix Arithmetic
Lecture 7: Introduction to Pandas
Lecture 8: Read in Data from CSV
Lecture 9: Read in Data from Excel
Lecture 10: Basic Data Cleaning
Chapter 3: Introduction to Keras
Lecture 1: What is Keras?
Lecture 2: Keras Installation-Windows
Lecture 3: Keras Installation on Mac OS
Lecture 4: Written Keras Installation Instructions
Chapter 4: Some Basic Concepts
Lecture 1: What is Machine Learning?
Chapter 5: Neural Networks With Keras
Lecture 1: Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks)
Lecture 2: Activation Functions
Lecture 3: Multi Layer Perceptron (MLP) With Keras
Lecture 4: What is Backpropagation?
Lecture 5: Keras MLP For Binary Classification
Lecture 6: Accuracy Assessment For Binary Classification
Lecture 7: Keras MLP for Multiclass Classification
Lecture 8: Keras MLP for Regression
Chapter 6: Unsupervised Learning With Keras
Lecture 1: What is Unsupervised Learning?
Lecture 2: Autoencoders for Unsupervised Classification
Lecture 3: Autoencoders in Keras (Sparsity Constraints)
Lecture 4: Autoencoders in Keras (Simple)
Lecture 5: Deep Autoencoder With Keras
Chapter 7: Deep Learning For Tensorflow & Keras
Lecture 1: DNN Classifier With Keras
Lecture 2: DNN Classifier With Keras-Example 2
Chapter 8: Convolution Neural Network (CNN) For Image Analysis
Lecture 1: Introduction to CNN
Lecture 2: CNN Workflow for Keras
Lecture 3: CNN With Keras
Lecture 4: CNN on Image Data with Keras-Part 1
Lecture 5: CNN on Image Data with Keras-Part 2
Lecture 6: Autoencoders for With CNN- Keras
Lecture 7: Posit On POSIT
Instructors
-
Minerva Singh
Bestselling Instructor & Data Scientist(Cambridge Uni)
Rating Distribution
- 1 stars: 15 votes
- 2 stars: 5 votes
- 3 stars: 15 votes
- 4 stars: 24 votes
- 5 stars: 116 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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